Free, no-auth-required search via public.api.bsky.app.
Always-on like HN and Polymarket (no API key needed).
- New scripts/lib/bluesky.py: search + parse via AT Protocol
- BlueskyItem schema, normalization, scoring, deduplication
- Wired into orchestrator ThreadPoolExecutor with timeout config
- Rendering in compact, full, and JSON output modes
- 14 unit tests covering parsing, dates, relevance, edge cases
- --search=bluesky / --search=bsky for bluesky-only mode
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
One SCRAPECREATORS_API_KEY now covers Reddit, TikTok, Instagram, AND X.
Priority: Bird (free) > xAI API > ScrapeCreators (shared key).
New module scrapecreators_x.py follows the same pattern as tiktok.py.
Updated env.py source routing and last30days.py orchestrator dispatch.
Includes 20 unit tests.
Fixes#55.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Xiaohongshu search via local MCP service (opt-in, zero impact if service not running)
- Reddit public JSON fallback (works with zero API keys)
- Reddit priority: ScrapeCreators -> OpenAI -> public fallback
- Updated env.py: Reddit always available via public fallback
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Resolve conflicts between ScrapeCreators Reddit (main) and
public Reddit fallback (PR #48). Priority: ScrapeCreators ->
OpenAI -> public Reddit fallback.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add --save-dir flag to last30days.py that saves raw research output
during the existing script run. Remove entire "Save Research to
Documents" section from SKILL.md (~45 lines). No more extra tool
calls, no (No output), no multi-minute cogitation after invitation.
Tested: --mock confirms file creation and duplicate date suffixing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- New scripts/lib/reddit.py: multi-query expansion, global search,
subreddit discovery, targeted subreddit search, comment enrichment
- 68 results in 17s vs ~15 results in 60-90s (OpenAI)
- Cost: ~$0.02/search vs $0.03-0.10 (15-50x cheaper)
- Real engagement data (score, comments, dates) from API
- No more 429 rate limits on comment enrichment
- Falls back to OpenAI if SCRAPECREATORS_API_KEY missing
- Registered as last30daysbeta for parallel local testing
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- add xiaohongshu/xhs source path via xiaohongshu-mcp HTTP API\n- add Reddit public JSON fallback when OpenAI auth is unavailable\n- update diagnostics/UI rendering for new source availability states\n- harden Xiaohongshu availability probe to reduce false negatives\n- include source status reporting for Xiaohongshu
Add Instagram Reels as the 8th research source via ScrapeCreators API.
One API key (SCRAPECREATORS_API_KEY) now covers both TikTok and Instagram.
- Add scripts/lib/instagram.py: keyword search, transcript extraction,
relevance scoring, engagement metrics (views, likes, comments)
- Add InstagramItem to schema, normalization, scoring, dedup, rendering
- Add Instagram to orchestrator pipeline, watchlist, and UI spinners
- Update SKILL.md: stats template, citation priority, item format,
URL-to-name extraction rules, anti-Sources instruction
- Update README and CHANGELOG for v2.8
- Fix: Instagram/TikTok not running in --search= web-only path
- Fix: web stats line showing full URLs instead of domain names
- Replace APIFY_API_TOKEN with SCRAPECREATORS_API_KEY throughout
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Root cause of empty TikTok results: Apify required monthly subscription.
ScrapeCreators is PAYG with 100 free credits and no subscription.
Key fix: ScrapeCreators nests items under aweme_info wrapper
(search_item_list[].aweme_info.{fields}), which the previous
implementation missed, causing all fields to be empty.
Changes:
- Rewrite tiktok.py to use ScrapeCreators REST API
- Add aweme_info unwrapping for correct field extraction
- Add transcript fetching via /video/transcript endpoint
- Add SCRAPECREATORS_API_KEY to env.py config
- Update last30days.py to use env.get_tiktok_token()
- Delete apify_client_wrapper.py (no longer needed)
- Update tests for new date field format (create_time)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Remove double quotes around $ARGUMENTS in SKILL.md so bash word-splits
the expansion, and change argparse topic from nargs="?" to nargs="*"
so multi-word topics still work. Also document --store, --include-web,
--diagnose, and --timeout flags in the Options section.
Closes#36
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
When running in Claude Code, the assistant has a built-in WebSearch tool
that's free and higher quality than Parallel AI/Brave/OpenRouter. Adding
--no-native-web to the SKILL.md invocation defers web search to the
assistant, saving API credits. OpenClaw invocations don't pass this flag,
so they continue using native web backends.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The websearch module import was dropped when the tiktok import was added,
causing the script to crash during the rendering phase after all data
was successfully collected.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add TikTok search, scoring, and rendering using the Apify platform
(clockworks/tiktok-scraper actor). Users bring their own APIFY_API_TOKEN
($5/month free credits, no CC required). The shared apify_client_wrapper
module is designed for reuse by future Facebook/Instagram sources.
- New modules: tiktok.py (search + caption extraction), apify_client_wrapper.py
- Schema: TikTokItem dataclass, shares field on Engagement, Report.tiktok
- Pipeline: normalize → filter → score → sort → dedupe → cross-link → render
- Scoring: 0.50*log1p(views) + 0.30*log1p(likes) + 0.20*log1p(comments)
- SKILL.md bumped to v2.7 with TikTok stats, citations, and security docs
- 26 unit tests covering relevance, normalize, score, dedupe, render, round-trip
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Inspired by PR #26 (wkbaran), whose early work on HN/YouTube sources helped
shape what we built in v2.5. Cherry-picks the source-filtering concept as a
clean implementation against our existing architecture.
--search=SOURCES accepts comma-separated: reddit, x, hn, youtube, polymarket, web
Example: --search reddit,hn (run only Reddit + Hacker News)
Also:
- bird_x: add noise words (trending, viral, plugin, skills) + last-chance retry
- render: show xAI tip for reddit-only mode regardless of missing_keys value
- tests: new test_bird_x.py (5 tests)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: fix YAML error in argument-hint
* add codex auth support to responses API
* Use gpt-5.1-codex-mini as default model for Codex auth
Add CODEX_FALLBACK_MODELS chain (gpt-5.1-codex-mini → gpt-5.2) for
Codex endpoint which doesn't support standard OpenAI models like
gpt-4o-mini. Adds model fallback retry on 400 errors in the Codex
search path. Also adds test_codex_auth.py with 22 unit tests covering
JWT decoding, auth resolution, SSE parsing, and payload building.
* Pass .env credentials to Bird Node subprocesses for X auth
On platforms without browser cookie access (e.g. WSL2), Bird's
vendored Node.js module cannot read AUTH_TOKEN/CT0 from Firefox
or Chrome cookie stores. The .env config file already supports
these values, but they were only loaded into the Python config
dict — never exported to the environment of Node subprocesses.
- Add AUTH_TOKEN/CT0 to env.py config key loading
- Add set_credentials()/\_subprocess_env() to bird_x.py to inject
credentials into the env dict passed to subprocess.run/Popen
- Call set_credentials() in main() before Bird auth detection
---------
Co-authored-by: Justin Williams <jblwilliams@gmail.com>
Search Polymarket's free Gamma API for relevant prediction markets on any
topic. Uses smart multi-query expansion to cast a wider net (e.g., "Arizona
Basketball" also searches "Arizona"), merges and dedupes by event ID, and
shows price movement context ("up 22.5% this week"). No API key required.
Also hides sources with zero results from the stats output (all sources).
54 new tests, all passing. Full pipeline integration with scoring, dedupe,
cross-source linking, and rendering.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The resolved handle dedup was wrong: if entity_extract found @thedorbrothers
(from @mentions in Phase 1 results), the resolved handle search was skipped
entirely. But entity-extracted handles are searched WITH topic keywords
(from:handle topic), while resolved handles need UNFILTERED search
(from:handle) to find posts that don't mention the topic string.
Example: Dor Brothers' viral tweet (5.5K likes) says "We made a $300M movie
starring @LoganPaul" - no mention of "dor brothers" anywhere. The topic-
filtered entity search missed it. The unfiltered resolved search finds it.
Before: 30 X posts, 161+ likes (entity search only)
After: 40 X posts, 5549+ likes (resolved handle adds viral tweet)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
When a topic is a person/brand (e.g. "Dor Brothers", "Jason Calacanis"),
the agent now resolves their X handle via WebSearch before running the
script, then passes --x-handle to search their posts unfiltered (no
topic keywords required). This finds posts the entity made without
mentioning their own name.
- SKILL.md + OpenClaw variant: Step 0.5 handle resolution instructions
- last30days.py: --x-handle CLI arg, passed through to _run_supplemental()
- bird_x.search_handles(): topic is now Optional[str] for unfiltered mode
- schema.py: resolved_x_handle field on Report
- render.py: show resolved handle in stats output
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
YouTube videos now get real relevance scores based on token overlap
between the search query and video title (was hardcoded at 0.7).
Uses ratio overlap with stopword removal, floored at 0.1.
Cross-source linking annotates items that discuss the same story
across different platforms (e.g., Reddit + HN + X). Items get
bidirectional cross_refs displayed as [xref: R3, HN5] in compact
output so Claude can triangulate multi-platform coverage.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add HN search via free Algolia API (no key needed). Two-phase approach:
search for stories, then enrich top ones with comments. Integrated into
the full pipeline (normalize, score, dedupe, render) running in parallel
with Reddit/X/YouTube. Source priority: Reddit > X > HN > YouTube > Web.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
OpenAI Responses API web_search takes 60-90s but the generic
future timeout was killing it at 30s (quick) / 60s (default).
Added reddit_future key to TIMEOUT_PROFILES (60/90/120s).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
YouTube: Add youtube_future timeout key (60/90/120s for quick/default/deep)
separate from the shared future timeout. YouTube needs more time because
it does search + parallel transcript fetching. Previously, 20 videos +
5 transcripts exceeded the 60s budget and all results were discarded.
Reddit 429: Propagate rate-limit errors instead of swallowing them.
Enrichment now uses 10s timeout / 1 retry (was 30s / 3 retries).
On first 429, cancel remaining enrichment and skip Phase 2 Reddit.
Total time wasted on 429 drops from ~75s to ~12s.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The hard date filter in the main script was double-filtering YouTube
results. youtube_yt.py already applies a soft date filter that prefers
recent videos but keeps older ones when < 3 are within range (for
evergreen topics like "youtube thumbnails"). The hard filter then
removed all of them, resulting in 0 YouTube items.
YouTube content has a longer shelf life than tweets/posts, so the
soft filter's fallback behavior is correct.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace CLI-style promo banners with casual, conversational NUX message
that teaches users to say "last30" + natural language. Remove stale Bird
CLI npm install references and dead prompt_bird_install methods.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Script was hanging indefinitely when API sources were slow or
unresponsive. Now enforces bounded execution:
- Global timeout watchdog (180s default, 90s --quick, 300s --deep)
- Per-source future.result() timeouts (60s/30s/90s by depth)
- Parallel Reddit enrichment capped at 15 items / 45s total
- Subprocess process-group isolation (os.setsid + killpg)
- atexit cleanup kills all tracked child processes
- --timeout=N flag for user override
Also fixes the UX gap where missing sources were silently skipped:
- Pre-flight diagnostic banner shows source status before research
- Source status footer in compact output shows used/skipped/why
- Actionable fix commands for each missing source
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- _search_web() dispatches to Parallel AI / Brave / OpenRouter based on config
- Web results flow through full pipeline: normalize → score → dedupe
- --diagnose shows all source availability (API keys, Bird, YouTube, web backends)
- --store persists findings to SQLite via store.py for watchlist/briefing system
- run_research() now returns web_items alongside reddit/x/youtube
- web_needed flag only set when no native web backend is available
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add agents/openai.yaml for Codex skill discovery
- Make SKILL.md script path portable (repo, Claude, Codex, agents dirs)
- Platform-neutral output text ("assistant" instead of "Claude")
- Sandbox-friendly cache/output dirs with env var overrides and tempdir fallback
- Add Codex installation docs to README
Inspired by PR #24 (el-analista) and PR #5 (jblwilliams).
Zero impact on existing Claude Code behavior.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
YouTube search and transcript extraction runs automatically when yt-dlp
is installed. Searches for topic videos from the last N days, fetches
auto-generated transcripts for top results, and feeds them through the
same scoring pipeline (relevance + recency + engagement) as Reddit/X.
New files:
- youtube_yt.py: search, transcript extraction, VTT cleanup
Modified files:
- schema.py: YouTubeItem dataclass, updated Report
- normalize.py: normalize_youtube_items()
- score.py: YouTube engagement scoring (views-dominated)
- dedupe.py: YouTube deduplication
- render.py: YouTube section in compact output
- env.py: is_ytdlp_available() check
- ui.py: YouTube progress messages
- last30days.py: _search_youtube(), parallel execution with Reddit/X
- SKILL.md: YouTube in stats box, citation priority
- README.md: YouTube docs, yt-dlp requirement, Peter shoutout
Inspired by Peter Steinberger's yt-dlp + summarize toolchain approach.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
After the initial broad search (Phase 1), extract key entities from results
and run targeted secondary searches to surface content the broad pass missed:
- New entity_extract.py: parses @handles, #hashtags, subreddits from results
- bird_x.py: search_handles() does targeted from:handle searches via Bird CLI
- openai_reddit.py: search_subreddits() uses Reddit's free .json search endpoint
- last30days.py: Phase 2 orchestration runs after enrichment, merges + dedupes
Tested with "kanye west" (+9 Reddit, +1 X) and "claude code skills" (+6 Reddit, +1 X).
Phase 2 is skipped on --quick mode. Default caps at 3 handles/subs, deep at 5.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Stats: replace BAD/GOOD examples with strict fill-in-the-blank template
- Reddit: add subreddit-targeted fallback search, soften scoring penalties
(engagement -10→-3, date confidence -10→-5), add minimum result guarantee
- Citations: limit to 1 per insight, short format, no engagement metrics
- Summary: add bold topic headers template for structured paragraphs
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
1. last30days.py: Check isinstance(dict) before .get() - Bird returns
list on success, dict on error
2. bird_x.py: Update field mappings for Bird's actual response format:
- author.username not user.screen_name
- createdAt not created_at (camelCase)
- likeCount, retweetCount, etc. (camelCase)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Remove interactive "Install Bird CLI?" prompt
- Add Bird as FREE option in promo messages
- Auto-detect Bird silently (use if authenticated)
- Keep original flow: show promo → continue with available sources
Bird now appears in the promo alongside API keys:
🔵 X (Twitter)
└─ FREE: npm install -g @steipete/bird (uses browser session)
└─ Or: Add XAI_API_KEY (paid API)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Move Bird CLI check to run before topic validation so users see
the install prompt even when running without a topic argument.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Move progress display initialization early to support Bird prompts
- Check Bird availability and offer install if no X source available
- Override available sources when Bird is ready
- Pass x_source parameter to run_research function
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add bird_x import and setup_bird_if_needed function to main script.
The function checks Bird status and offers installation if needed,
returning 'bird' if ready, 'declined' if user declined, or None if
unavailable.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Refactor run_research() to use ThreadPoolExecutor for parallel execution
- Reddit timeout/crash no longer blocks X search from running
- Add catch for ConnectionResetError/OSError in http.py
- Per-item error handling in Reddit enrichment (one failure doesn't crash all)
- Increase API timeouts from 60/90/120 to 90/120/180 seconds
- Add ClawdBot setup example to README
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
If initial search returns <5 threads, extract core subject and retry:
- "best nano banana prompting practices" → retry with "nano banana"
- Combines results from both searches, deduped by URL
Note: OpenAI's web_search still tends to find old content. This retry
helps cast a wider net but doesn't fully solve the recency issue.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Skill now works without any API keys using WebSearch fallback
- Shows promo banner marketing Reddit/X data when keys are missing
- Partial mode (one key) shows shorter tip for the missing source
- Updated SKILL.md to document three modes: Full, Partial, Web-Only
- Added get_missing_keys() to env.py for promo logic
- Added show_promo(), start_web_only(), show_web_only_complete() to ui.py
- Updated render_compact() to include inline promo for web-only mode
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Previously Reddit was returning ~60% old content (some from 2022).
This commit adds multiple layers of date enforcement:
- Reddit prompt: Explicit from_date/to_date with "fewer results > older results"
- Hard filter: filter_by_date_range() in normalize.py excludes old content
- WebSearch Date Detective: Extracts dates from URLs (/2026/01/24/) and
snippets ("January 24, 2026", "3 days ago")
- WebSearch scoring: +10 bonus for verified dates, -20 penalty for unknown
The skill now guarantees only content from the last 30 days.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add Claude's built-in WebSearch tool as a third research source for
/last30days. This enables the skill to work out of the box with zero
API keys while preserving Reddit/X as the primary sources.
Key changes:
- Add WebSearchItem schema for web results (no engagement metrics)
- Add score_websearch_items() with 55/45 relevance/recency weighting
- Apply -15pt source penalty so WebSearch ranks below Reddit/X
- Add --include-web CLI flag to opt-in to WebSearch
- Return 'web' mode when no API keys configured (zero-config)
- Update render.py with [WEB] source label formatting
When WebSearch is enabled, the script outputs instructions for Claude
to use its built-in WebSearch tool, then synthesize results together.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add LAST30DAYS_DEBUG env var / --debug flag
- Log HTTP requests, responses, and errors
- Show API error details when debug enabled
- Helps diagnose API failures
Usage: python3 last30days.py "topic" --debug
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Wrap xAI search in try/except like Reddit
- Show error message but continue with Reddit results
- Parse function checks for API errors before processing
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Show "⚡ CACHED RESULTS (Xh old)" in compact output header
- Add "use --refresh for fresh data" hint
- Track from_cache and cache_age_hours in Report schema
- Update UI to show cache age in stderr message
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- New ui.py module with colored output and animations
- Animated spinner during Reddit/X searches
- Progress tracking for enrichment phase [1/N]
- Fun random status messages per phase
- Mini ASCII banner at start
- Completion summary with timing
Makes the research feel more alive while waiting!
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The Report.to_dict() serializes range as {from, to} but constructor
expects range_from/range_to. Added from_dict() classmethod to properly
deserialize cached data, reconstructing all nested objects (Engagement,
Comment, SubScores, RedditItem, XItem).
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Matt Van Horn